Testing and Optimizing the Drude Polarizable Force Field for Blocked Amino Acids Based on High-Level Quantum-Mechanical Energy Surfaces

The correct reproduction of conformational substates of amino acids was tested for the CHARMM Drude polarizable force field. This was achieved by evaluating the reorganization energies for all low lying energy minima occurring in all 15 neutral blocked amino acids on a quantum-mechanical (QM) energy surface at the MP2/cc-pVDZ level. The results indicate that the bonded parameters of the N-acetyl (ACE) and N-Methylamide (CT3) blocking groups lead to significant discrepancies. A reparametrization of five bond angles significantly improved the agreement with the QM energy surface. The corrected Drude force field exhibits almost the same average reorganization energies relative to the MP2 energy surface as the AM1 and PM3 semi-empirical methods.

Conformational Flexibility and Local Frustration in the Functional States of the SARS-CoV-2 Spike B.1.1.7 and B.1.351 Variants: Mutation-Induced Allosteric Modulation Mechanism of Functional Dynamics and Protein Stability

The experimental and computational studies of the SARS-CoV-2 spike protein variants revealed an important role of the D614G mutation that is shared across variants of concern(VOCs), linking the effect of this mutation with the enhanced virus infectivity and transmissibility. The recent structural and biophysical studies characterized the closed and open states of the B.1.1.7 (B.1.1.7) and B.1.351 (Beta) spike variants allowing for a more detailed atomistic characterization of the conformational landscapes and functional changes. In this study, we employed coarse-grained simulations of the SARS-CoV-2 spike variant trimers together with the ensemble-based mutational frustration analysis to characterize the dynamics signatures of the conformational landscapes. By combining the local frustration analysis of the conformational ensembles with collective dynamics and residue-based mutational scanning of protein stability, we determine protein stability hotspots and identify potential energetic drivers favoring the receptor-accessible open spike states for the B.1.1.7 and B.1.351 spike variants. Through mutational scanning of protein stability changes we quantify mutational adaptability of the S-G614, S-B.1.1.7 and S-B.1.351 variants in different functional forms. Using this analysis, we found a significant conformational and mutational plasticity of the open states for all studied variants. The results of this study suggest that modulation of the energetic frustration at the inter-protomer interfaces can serve as a mechanism for allosteric couplings between mutational sites, the inter-protomer hinges of functional motions and motions of the receptor-binding domain required for binding of the host cell receptor. The proposed mechanism of mutation-induced energetic frustration may result in the greater adaptability and the emergence of multiple conformational substates in the open form. This study also suggested functional relationships between mutation-induced modulation of protein dynamics, local frustration and allosteric regulation of the SARS-CoV-2 spike protein.

The Landscape-Based Protein Stability Analysis and Network Modeling of Multiple Conformational States of the SARS-CoV-2 Spike D614 Mutant: Conformational Plasticity and Frustration-Driven Allostery as Energetic Drivers of Highly Transmissible Spike Variant

The structural and functional studies of the SARS-CoV-2 spike protein variants revealed an important role of the D614G mutation that is shared across many variants of concern(VOCs), suggesting the effect of this mutation on the enhanced virus infectivity and transmissibility. The recent structural and biophysical studies provided important evidence about multiple conformational substates of the D614G spike protein. The development of a plausible mechanistic model which can explain the experimental observations from a more unified thermodynamic perspective is an important objective of the current work. In this study, we employed efficient and accurate coarse-grained simulations of multiple structural substates of the D614G spike trimers together with the ensemble-based mutational frustration analysis to characterize the dynamics signatures of the conformational landscapes. By combining the local frustration profiling of the conformational states with residue-based mutational scanning of protein stability and network analysis of allosteric interactions and communications, we determine the patterns of mutational sensitivity in the functional regions and sites of variants. We found that the D614G mutation may induce a considerable conformational adaptability of the open states in the SARS-CoV-2 spike protein without compromising folding stability and integrity of the spike protein. The results suggest that the D614G mutant may employ a hinge-shift mechanism in which the dynamic couplings between the site of mutation and the inter-protomer hinge modulate the inter-domain interactions, global mobility change and the increased stability of the open form. This study proposes that mutation-induced modulation of the conformational flexibility and energetic frustration at the inter-protomer interfaces may serve as an efficient mechanism for allosteric regulation of the SARS-CoV-2 spike proteins.

Multiscale simulations identify origins of differential carbapenem hydrolysis by the OXA-48 β-lactamase

OXA-48 β-lactamases are frequently encountered in bacterial infections caused by carbapenem-resistant Gram-negative bacteria. Due to the importance of carbapenems in treatment of healthcare-associated infections, and the increasingly wide dissemination of OXA-48-like enzymes on plasmids, these β-lactamases are of high clinical significance. Notably, OXA-48 hydrolyses imipenem more efficiently than other commonly used carbapenems, such as meropenem. Here, we use extensive multi-scale simulations of imipenem and meropenem hydrolysis by OXA-48 to dissect the dynamics and to explore differences in reactivity of the possible conformational substates of the respective acylenzymes. QM/MM simulations of the deacylation reaction for both substrates demonstrate that deacylation is favoured when the 6α-hydroxyethyl group is able to hydrogen bond to the water molecule responsible for deacylation, but disfavoured by increasing hydration of either oxygen of the carboxylated Lys73 general base. Differences in free energy barriers calculated from the QM/MM simulations correlate well with the experimentally observed differences in hydrolytic efficiency between meropenem and imipenem. We conclude that the impaired breakdown of meropenem, compared to imipenem, which arises from a subtle change in the hydrogen bonding pattern between the deacylating water molecule and the antibiotic, is most likely induced by the meropenem 1-methyl group. In addition to increased insights into carbapenem breakdown by OXA β-lactamases, which may aid design of new antibiotics or inhibitors, our approach exemplifies the combined use of atomistic simulations in determining the possible different enzyme-substrate substates, and their influence on enzyme reaction kinetics.

Impact of Conformational Substates and Energy Landscapes on Understanding Hemoglobin Kinetics and Function

Hans Frauenfelder’s discovery of conformational substates in studies of myoglobin carbon monoxide geminate rebinding kinetics at cryogenic temperatures (Austin RH, Beeson KW, Eisenstein L, Frauenfelder H, & Gunsalus IC (1975) Dynamics of Ligand Binding to Myoglobin. Biochemistry 14(24):5355–5373) followed by his introduction of energy landscape theory with Peter Wolynes (Frauenfelder H, Sligar SG, & Wolynes PG (1991) The Energy Landscapes and Motions of Proteins. Science 254(5038):1598–1603) marked the beginning of a new era in the physics and physical chemistry of proteins. Their work played a major role in demonstrating the power and importance of dynamics and of Kramers reaction rate theory for understanding protein function. The biggest impact of energy landscape theory has been in the protein folding field, which is well-known and has been documented in numerous articles and reviews, including a recent one of my own (Eaton WA (2021) Modern Kinetics and Mechanism of Protein Folding: a Retrospective. J. Phys. Chem. B. 125(14):3452–3467). Here I will describe the much less well-known impact of their modern view of proteins on both experimental and theoretical studies of hemoglobin kinetics and function. I will first describe how Frauenfelder’s experiments motivated and influenced my own research on myoglobin, which were key ingredients to my work on understanding hemoglobin.

Nanopore tweezers measurements of RecQ conformational changes reveal the energy landscape of helicase motion

Helicases are essential for nearly all nucleic acid processes across the tree of life. Using Nanopore Tweezers we observed the small, fast steps taken by single RecQ helicases as they step along and unwind DNA at ultrahigh spatiotemporal resolution. By directly measuring conformational substates of RecQ we determine the coupling between helicase domain motions and chemical reactions that together produce forward motion along the DNA. Application of assisting and opposing forces shows that RecQ has a highly asymmetric energy landscape that reduces its sensitivity to opposing mechanical forces that could be encountered in vivo by molecular roadblocks such as DNA bound proteins. This energy landscape enables RecQ to maintain speed against an opposing load.

Highly Dynamic Polynuclear Metal Cluster Revealed in a Single Metallothionein Molecule

Human metallothionein (MT) is a small-size yet efficient metal-binding protein, playing an essential role in metal homeostasis and heavy metal detoxification. MT contains two domains, each forming a polynuclear metal cluster with an exquisite hexatomic ring structure. The apoprotein is intrinsically disordered, which may strongly influence the clusters and the metal-thiolate (M-S) bonds, leading to a highly dynamic structure. However, these features are challenging to identify due to the transient nature of these species. The individual signal from dynamic conformations with different states of the cluster and M-S bond will be averaged and blurred in classic ensemble measurement. To circumvent these problems, we combined a single-molecule approach and multiscale molecular simulations to investigate the rupture mechanism and chemical stability of the metal cluster by a single MT molecule, focusing on the Zn4S11 cluster in the α domain upon unfolding. Unusual multiple unfolding pathways and intermediates are observed for both domains, corresponding to different combinations of M-S bond rupture. None of the pathways is clearly preferred suggesting that unfolding proceeds from the distribution of protein conformational substates with similar M-S bond strengths. Simulations indicate that the metal cluster may rearrange, forming and breaking metal-thiolate bonds even when MT is folded independently of large protein backbone reconfiguration. Thus, a highly dynamic polynuclear metal cluster with multiple conformational states is revealed in MT, responsible for the binding promiscuity and diverse cellular functions of this metal-carrier protein.

Accurate modeling of DNA conformational flexibility by a multivariate Ising model

The sequence-dependent structure and deformability of DNA play a major role for binding of proteins and regulation of gene expression. So far, most efforts to model DNA flexibility are based on unimodal harmonic stiffness models at base-pair resolution. However, multimodal behavior due to distinct conformational substates also contributes significantly to the conformational flexibility of DNA. Moreover, these local substates are correlated to their nearest-neighbor substates. A description for DNA elasticity which includes both multimodality and nearest-neighbor coupling has remained a challenge, which we solve by combining our multivariate harmonic approximation with an Ising model for the substates. In a series of applications to DNA fluctuations and protein–DNA complexes, we demonstrate substantial improvements over the unimodal stiffness model. Furthermore, our multivariate Ising model reveals a mechanical destabilization for adenine (A)-tracts to undergo nucleosome formation. Our approach offers a wide range of applications to determine sequence-dependent deformation energies of DNA and to investigate indirect readout contributions to protein–DNA recognition.